Detail publikace
Reducing Domain mismatch in Self-supervised speech pre-training
BASKAR, M. ROSENBERG, A. RAMABHADRAN, B. ZHANG, Y.
Originální název
Reducing Domain mismatch in Self-supervised speech pre-training
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Masked speech modeling (MSM) methods such as wav2vec2
or w2v-BERT learn representations over speech frames which
are randomly masked within an utterance. While these methods
improve performance of Automatic Speech Recognition (ASR)
systems, they have one major limitation. They treat all unsupervised
speech samples with equal weight, which hinders learning
as not all samples have relevant information to learn meaningful
representations. In this work, we address this limitation. We
propose ask2mask (ATM), a novel approach to focus on specific
samples during MSM pre-training. ATM employs an external
ASR model or scorer to weight unsupervised input samples by
performing a fine-grained data selection. ATM performs masking
over the highly confident input frames as chosen by the scorer.
This allows the model to learn meaningful representations. We
conduct fine-tuning experiments on two well-benchmarked corpora:
LibriSpeech (matching the pre-training data) and, AMI
and CHiME-6 (not matching the pre-training data). The results
substantiate the efficacy of ATM on significantly improving the
recognition performance under mismatched conditions while
still yielding modest improvements under matched conditions.
Klíčová slova
Self-supervision, Wav2vec2, pretraining, Data selection, Domain mismatch, asr, speech recognition
Autoři
BASKAR, M.; ROSENBERG, A.; RAMABHADRAN, B.; ZHANG, Y.
Vydáno
18. 9. 2022
Nakladatel
International Speech Communication Association
Místo
Incheon
ISSN
1990-9772
Periodikum
Proceedings of Interspeech
Číslo
9
Stát
Francouzská republika
Strany od
3028
Strany do
3032
Strany počet
5
URL
BibTex
@inproceedings{BUT179828,
author="Murali Karthick {Baskar} and Andrew {Rosenberg} and Bhuvana {Ramabhadran} and Yu {Zhang}",
title="Reducing Domain mismatch in Self-supervised speech pre-training",
booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
year="2022",
journal="Proceedings of Interspeech",
number="9",
pages="3028--3032",
publisher="International Speech Communication Association",
address="Incheon",
doi="10.21437/Interspeech.2022-736",
issn="1990-9772",
url="https://www.isca-speech.org/archive/pdfs/interspeech_2022/baskar22_interspeech.pdf"
}
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